Instructions to use shahidul034/drug_sentiment_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shahidul034/drug_sentiment_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shahidul034/drug_sentiment_analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shahidul034/drug_sentiment_analysis") model = AutoModelForSequenceClassification.from_pretrained("shahidul034/drug_sentiment_analysis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aed1c8cf846a42949384eb3ac4b85b3102663d1e14f0357e955716ce59abf813
- Size of remote file:
- 4.28 kB
- SHA256:
- c13846a30142be7084a3e344360a22030641974fd7e529151d1fd012ae39c30c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.